Large data sets may exist in various levels of size and organization. With big data comprising data sets as large as ever, the volume of data collected incident to the increased popularity of online and electronic transactions continues to grow. Billions of rows and hundreds of thousands of columns worth of data may populate a single table, for example. The large volume of data may be collected in a raw, unstructured, and undescriptive format in some instances. The large volume of unorganized information may not be informative to users without some sort of processing to identify patterns and trends in the data. For example, an unaided user may look at a big data set, without being able to decipher the name of a field, whether the field is unique, how the field is populated, what type of data the field contains, and/or any other details about the field. Without meaningful descriptors of the columns and cells, the collection of data may not be beneficial to a user. However, the size and varied structure of big data sets is typically incompatible with traditional data analysis techniques.